[PRE REVIEW]: quickBayes: An analytical approach to Bayesian loglikelihoods

[editorialbot]

Submitting author: !--author-handle-->@AnthonyLim23<!--end-author-handle-- (Anthony Lim) Repository: https://github.com/ISISNeutronMuon/quickBayes Branch with paper.md (empty if default branch): 82_paper Version: 1.0.0b18 Editor: !--editor-->@osorensen<!--end-editor-- Reviewers: @JonasMoss, @mattpitkin, @prashjet Managing EiC: Arfon Smith

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Software report:

github.com/AlDanial/cloc v 1.88  T=0.08 s (1208.5 files/s, 124040.1 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
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Python                          69           1537           2092           5281
reStructuredText                16            201            316            279
YAML                             8             39             15            220
Markdown                         3             22              0             62
TeX                              1              3              0             39
DOS Batch                        1              8              1             26
make                             1              4              7              9
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SUM:                            99           1814           2431           5916
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gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 664

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1103/RevModPhys.83.943 is OK

MISSING DOIs

- None

INVALID DOIs

- https://doi.org/10.1016/0921-4526(92)90036-R is INVALID because of 'https://doi.org/' prefix

[editorialbot]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[editorialbot]

Five most similar historical JOSS papers:

logKDE: log-transformed kernel density estimation Submitting author: @hiendn Handling editor: @arfon (Active) Reviewers: @strengejacke Similarity score: 0.8190

univariateML: An R package for maximum likelihood estimation of univariate densities Submitting author: @JonasMoss Handling editor: @arfon (Active) Reviewers: @MaaniBeigy, @vbaliga Similarity score: 0.8168

VBLinLogit: Variational Bayesian linear and logistic regression Submitting author: @jdrugo Handling editor: @usethedata (Retired) Reviewers: @ManuelaS, @usethedata Similarity score: 0.8150

bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework Submitting author: @DominiqueMakowski Handling editor: @cMadan (Active) Reviewers: @paul-buerkner, @tjmahr Similarity score: 0.8121

Bayesian X-ray Analysis (BXA) v4.0 Submitting author: @JohannesBuchner Handling editor: @jgostick (Active) Reviewers: @cescalara, @cescalara, @grburgess Similarity score: 0.8113

⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

[AnthonyLim23]

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[AnthonyLim23]

@editorialbot check references

[editorialbot]

Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1016/0921-4526(92)90036-R is OK
- 10.1103/RevModPhys.83.943 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[arfon]

@AnthonyLim23 - thanks for your submission to JOSS. We're currently managing a large backlog of submissions and the editor most appropriate for your area is already rather busy.

For now, we will need to waitlist this paper and process it as the queue reduces. Thanks for your patience!

[osorensen]

@arfon, I'm happy to edit this one

[osorensen]

@editorialbot add @osorensen as editor

[editorialbot]

Assigned! @osorensen is now the editor

[osorensen]

@editorialbot generate pdf

[editorialbot]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[editorialbot]

Five most similar historical JOSS papers:

logKDE: log-transformed kernel density estimation Submitting author: @hiendn Handling editor: @arfon (Active) Reviewers: @strengejacke Similarity score: 0.8180

univariateML: An R package for maximum likelihood estimation of univariate densities Submitting author: @JonasMoss Handling editor: @arfon (Active) Reviewers: @MaaniBeigy, @vbaliga Similarity score: 0.8159

VBLinLogit: Variational Bayesian linear and logistic regression Submitting author: @jdrugo Handling editor: @usethedata (Retired) Reviewers: @ManuelaS, @usethedata Similarity score: 0.8153

bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework Submitting author: @DominiqueMakowski Handling editor: @cMadan (Active) Reviewers: @paul-buerkner, @tjmahr Similarity score: 0.8121

Bayesian X-ray Analysis (BXA) v4.0 Submitting author: @JohannesBuchner Handling editor: @jgostick (Active) Reviewers: @cescalara, @cescalara, @grburgess Similarity score: 0.8105

⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

[osorensen]

@AnthonyLim23, I've opened an issue in the source repository with some comments on the submitted paper. Please report here when done.

[osorensen]

👋 @JohannesBuchner, @tddesjardins, @benjaminrose, would any of you be willing to review this submission for JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

[arfon]

@arfon, I'm happy to edit this one

✨ thank you @osorensen!

[AnthonyLim23]

@editorialbot generate pdf

[editorialbot]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[editorialbot]

Five most similar historical JOSS papers:

univariateML: An R package for maximum likelihood estimation of univariate densities Submitting author: @JonasMoss Handling editor: @arfon (Active) Reviewers: @MaaniBeigy, @vbaliga Similarity score: 0.8174

logKDE: log-transformed kernel density estimation Submitting author: @hiendn Handling editor: @arfon (Active) Reviewers: @strengejacke Similarity score: 0.8169

VBLinLogit: Variational Bayesian linear and logistic regression Submitting author: @jdrugo Handling editor: @usethedata (Retired) Reviewers: @ManuelaS, @usethedata Similarity score: 0.8154

Bayesian X-ray Analysis (BXA) v4.0 Submitting author: @JohannesBuchner Handling editor: @jgostick (Active) Reviewers: @cescalara, @cescalara, @grburgess Similarity score: 0.8144

bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework Submitting author: @DominiqueMakowski Handling editor: @cMadan (Active) Reviewers: @paul-buerkner, @tjmahr Similarity score: 0.8122

⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

[AnthonyLim23]

@editorialbot generate pdf

[editorialbot]

:point_right::page_facing_up: Download article proof :page_facing_up: View article proof on GitHub :page_facing_up: :point_left:

[editorialbot]

Five most similar historical JOSS papers:

univariateML: An R package for maximum likelihood estimation of univariate densities Submitting author: @JonasMoss Handling editor: @arfon (Active) Reviewers: @MaaniBeigy, @vbaliga Similarity score: 0.8183

logKDE: log-transformed kernel density estimation Submitting author: @hiendn Handling editor: @arfon (Active) Reviewers: @strengejacke Similarity score: 0.8180

VBLinLogit: Variational Bayesian linear and logistic regression Submitting author: @jdrugo Handling editor: @usethedata (Retired) Reviewers: @ManuelaS, @usethedata Similarity score: 0.8161

Bayesian X-ray Analysis (BXA) v4.0 Submitting author: @JohannesBuchner Handling editor: @jgostick (Active) Reviewers: @cescalara, @cescalara, @grburgess Similarity score: 0.8146

bayestestR: Describing Effects and their Uncertainty, Existence and Significance within the Bayesian Framework Submitting author: @DominiqueMakowski Handling editor: @cMadan (Active) Reviewers: @paul-buerkner, @tjmahr Similarity score: 0.8132

⚠️ Note to editors: If these papers look like they might be a good match, click through to the review issue for that paper and invite one or more of the authors before considering asking the reviewers of these papers to review again for JOSS.

[AnthonyLim23]

@osorensen I have updated the manuscript based on your comments. The latest generated PDF includes the changes.

[osorensen]

:wave: @JonasMoss, @jdrugo, @hiendn, would any of you be willing to review this submission for JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

[jdrugo]

@osorensen Unfortunately, I currently have too many other things on my plate to review the submission. I wouldn't be able to start with it before the end of January. Sorry.

[hiendn]

Hi @osorensen, unfortunately, I don't have time to do a review at the moment.

[JonasMoss]

Sure, I'd be happy to.

On Sat, Jan 13, 2024 at 8:57 PM Øystein Sørensen @.***> wrote:

👋 @JonasMoss https://github.com/JonasMoss, @jdrugo https://github.com/jdrugo, @hiendn https://github.com/hiendn, would any of you be willing to review this submission for JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

— Reply to this email directly, view it on GitHub https://github.com/openjournals/joss-reviews/issues/6106#issuecomment-1890753010, or unsubscribe https://github.com/notifications/unsubscribe-auth/AFZK3A6ANNXSVCPAUJEKL7DYOLRJJAVCNFSM6AAAAABADAN6ISVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTQOJQG42TGMBRGA . You are receiving this because you were mentioned.Message ID: @.***>

[osorensen]

Thanks for responding, @jdrugo and @hiendn.

[osorensen]

@editorialbot add @JonasMoss as reviewer

[editorialbot]

@JonasMoss added to the reviewers list!

[osorensen]

👋 @dgerosa, @prashjet, @mattpitkin, would any of you be willing to review this submission for JOSS? We carry out our checklist-driven reviews here in GitHub issues and follow these guidelines: https://joss.readthedocs.io/en/latest/review_criteria.html

[mattpitkin]

@osorensen I'm happy to review this

[osorensen]

@editorialbot add @mattpitkin as reviewer

[editorialbot]

@mattpitkin added to the reviewers list!

[prashjet]

Hi @osorensen - I'm happy to review this if still necessary, but I can only provide a response by late Feb at the earliest.

[osorensen]

Thanks @prashjet, that's absolutely fine.

[osorensen]

@editorialbot add @prashjet as reviewer

[editorialbot]

@prashjet added to the reviewers list!

[osorensen]

@editorialbot start review

[editorialbot]

OK, I've started the review over in https://github.com/openjournals/joss-reviews/issues/6230.